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Beyond the mouse: 3R-guided alternative animal models transforming cancer research

Comprehensively understanding cancer biology requires complex model systems, typically animal models, to replicate tumor behavior, microenvironment interactions, and cell migration/metastatic processes. Traditionally, genetically engineered and xenograft mouse models have been the cornerstone of can...

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Autori principali: Faehling, Tobias (Autore) , Reiff, Tobias (Autore) , Schumacher, Björn (Autore) , Arndt, Richard (Autore) , Amatruda, James F. (Autore) , Grünewald, Thomas G. P. (Autore) , Cidre-Aranaz, Florencia (Autore)
Natura: Article (Journal)
Lingua:inglese
Pubblicazione: 2026
In: Molecular cancer
Year: 2026, Volume: 25, Pages: 1-24
ISSN:1476-4598
DOI:10.1186/s12943-026-02601-0
Accesso online:Verlag, kostenfrei, Volltext: https://doi.org/10.1186/s12943-026-02601-0
Testo
Note sull'autore:Tobias Faehling, Tobias Reiff, Björn Schumacher, Richard Arndt, James F. Amatruda, Thomas G. P. Grünewald, Florencia Cidre-Aranaz
Descrizione
Riassunto:Comprehensively understanding cancer biology requires complex model systems, typically animal models, to replicate tumor behavior, microenvironment interactions, and cell migration/metastatic processes. Traditionally, genetically engineered and xenograft mouse models have been the cornerstone of cancer research. In recent years, the 3R principle—Replacement, Reduction, and Refinement—has reshaped ethical cancer research by promoting alternative animal models. Here we critically examine in vitro and in silico as well as four 3R-compliant animal models — the chicken chorioallantoic membrane (CAM) model, Danio rerio, Drosophila melanogaster, and Caenorhabditis elegans — and assess their advantages, limitations, and translational relevance for cancer research. Special emphasis is placed on practical considerations to inform optimal decision-making, including reproducibility and model-specific advantages and challenges. This review aims to support researchers in selecting ethical and effective preclinical models to advance cancer research.
Descrizione del documento:Online veröffentlicht: 26. März 2026
Gesehen am 21.08.2026
Descrizione fisica:Online Resource
ISSN:1476-4598
DOI:10.1186/s12943-026-02601-0

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